Systems and methods for optimizing sounding interval

ABSTRACT

Systems and methods are disclosed for optimizing the sounding interval in a MIMO communications system. Following a channel sounding protocol, net throughput may be estimated over time. The sounding interval may correspond to the period of time between the end of the sounding protocol and a time when the estimated net throughput is maximized. Estimating net throughput may involve estimating the number of bits that may be successfully transmitted divided by the time required to transmit. The number of bits that may be successfully transmitted may be estimated from a statistical channel profile including goodput.

FIELD OF THE PRESENT DISCLOSURE

This disclosure generally relates to wireless communication systems andmore specifically to systems and methods for statistically estimatingchannel characteristics.

BACKGROUND

A current area of development in wireless communications systemsinvolves the use of transmitters and receivers having multiple antennas.Generally, these are known as multiple-input multiple-output (MIMO)systems and offer increased peak data rate, spectral efficiency, andquality of service though the use of a plurality of parallel datastreams.

Relative to other wireless technologies, MIMO may enable substantialgains in both system capacity and transmission reliability withoutrequiring an increase in frequency spectrum resources. By increasing thenumber of transmit and receive antennas, the capacity of a MIMO channelmay be increased while also reducing the probability of all sub-channelsbetween the transmitter and receiver fading simultaneously. However,recovery of transmitted information in a MIMO system may be relativelymore complex and correspondingly benefit from accurate characterizationof the channel. Accordingly, any of a variety of channel models may beused to tailor aspects of the operation of the transceiver to helpoptimize performance. Further, the characteristics of the channel mayvary over time, which may warrant selecting different models to moreaccurately characterize the channel. In particular, operation in multiuser (MU) MIMO mode may be relatively sensitive to the channelstatistics. It would therefore be desirable to determine channelstatistics in order to allow improved operation of the system.

Another aspect of the operation of MIMO systems is the capability tooperate in a variety of modes. MIMO systems can be divided intooperational classes including single-user MIMO (SU MIMO) and multi-userMIMO (MU MIMO). Further MU MIMO modes may be subdivided depending uponthe number of users receiving the transmission. For example, MU2 mayrefer to a MU MIMO mode involving a simultaneous transmission to twousers, and more generally, MUn may involve transmission to n users. Anobjective of SU MIMO operation may be to increase peak data rate perterminal, whereas an objective in MU MIMO may be to increase sector (orservice cell) capacity. Operation in each of these classes hascorresponding advantages. For example, SU MIMO exploits spatialmultiplexing to provide increased throughput and reliability, while MUMIMO exploits multi-user multiplexing (or multi-user diversity) tofurther gains in capacity. Additionally, MU MIMO benefits from spatialmultiplexing even when employing a receiver having a single antenna. Assuch, it would be desirable for the MIMO system to select from theavailable operating modes in order to improve overall performance of thesystem.

Due to the complexity associated with providing multiple transmitstreams having adjusted phase and amplitude, MIMO systems rely on havingaccurate and current channel state information (CSI). In a closed-loopbeamforming system, the channel may be estimated using a soundingprotocol. By sending a known pattern of information, characteristics ofthe signal appearing at the receiver may be used to determine the CSI,which is then fed back to the transmitter. However, the transmission ofthe sounding signal represents overhead that may limit the overallthroughput of the system. Since the benefit of providing current CSI byperforming more frequent sounding protocols is offset by the increase inoverhead, it would be desirable to select a sounding interval thatoptimizes performance.

This disclosure satisfies the goals identified above as well as othergoals and needs.

SUMMARY

This disclosure includes methods for communication in a multiple inputmultiple output (MIMO) system. One suitable method includes performing achannel sounding protocol over a sounding time, estimating netthroughput over time following the channel sounding protocol,identifying a time corresponding to a maximum net throughput, anddetermining a sounding interval corresponding to a period of timebetween an end of the sounding protocol and the time corresponding tothe maximum net throughput. Further, a plurality of bins may be defined,beginning with a first bin and extending from the end of the soundingprotocol.

In one aspect, estimating net throughput over time may includeestimating a number of bits that may be successfully transmitted in eachbin, selecting a second bin subsequent to the first bin, summing bitsthat may be successfully transmitted during the first bin, during thesecond bin and during any intervening bins between the first bin and thesecond bin and dividing the summed bits by a duration of time extendingfrom the first bin to the second bin plus the sounding time. Further,identifying the time corresponding to the maximum net throughput mayinclude selecting the second bin such that net throughput at the secondbin is the maximum net throughput.

In one embodiment, estimating the number of bits that may besuccessfully transmitted in each bin may include statisticallydetermining goodput for each bin. Accordingly, statistically determininggoodput may include transmitting a first plurality of packets ofinformation over at least one preceding sounding interval initiated byperforming a sounding protocol, wherein each packet has a transmissiontime, is addressed to at least one station and is transmitted in atleast one MIMO mode, binning each packet of information in one bin ofthe plurality of bins based, at least in part, on the transmission timeof each packet relative to the sounding protocol of the at least onepreceding sounding interval, and determining a goodput valuecorresponding to the bin, the station and the MIMO mode for each packetthat is acknowledged.

In one aspect, determining the sounding interval may include multiplyinga number of bins between the first bin and the second bin, inclusive, bya duration of each bin.

The disclosure also includes systems for wireless communication. Forexample, a wireless communications device configured to operate in amultiple input multiple output (MIMO) system may have a plurality oftransmitter units and a statistics estimator, wherein the transmitterunits are configured to transmit a channel sounding protocol over asounding time and wherein the statistics estimator is configured toestimate net throughput over time following the channel soundingprotocol, identify a time corresponding to a maximum net throughput, anddetermine a sounding interval corresponding to a period of time betweenan end of the sounding protocol and the time corresponding to themaximum net throughput. Further, the statistics estimator may define aplurality of bins beginning with a first bin and extending from the endof the sounding protocol. The statistics estimator may also estimate netthroughput over time by estimating a number of bits that may besuccessfully transmitted in each bin, selecting a second bin subsequentto the first bin, summing bits that may be successfully transmittedduring the first bin, during the second bin and during any interveningbins between the first bin and the second bin and dividing the summedbits by a duration of time extending from the first bin to the secondbin plus the sounding time. In addition, the statistics estimator isconfigured to identify the time corresponding to the maximum netthroughput by selecting the second bin such that net throughput at thesecond bin is the maximum net throughput.

In one embodiment, the statistics estimator may estimate the number ofbits that may be successfully transmitted in each bin based, at least inpart, on a statistically determined goodput for each bin. Further, thetransmitter units may transmit a first plurality of packets ofinformation over at least one preceding sounding interval initiated byperforming a sounding protocol, wherein each packet has a transmissiontime, is addressed to at least one station and is transmitted in atleast one MIMO mode and the statistics estimator may determine goodputby binning each packet of information in one bin of the plurality ofbins based, at least in part, on the transmission time of each packetrelative to the sounding protocol of the at least one preceding soundinginterval and determining a goodput value corresponding to the bin, thestation and the MIMO mode for each packet that is acknowledged.

In one aspect, the statistics estimator may determine the soundinginterval by multiplying a number of bins between the first bin and thesecond bin, inclusive, by a duration of each bin.

The disclosure also includes a non-transitory processor-readable storagemedium for operating a multiple input multiple output (MIMO) wirelesscommunications device having instructions including instructions tocause the wireless communications device to perform a channel soundingprotocol over a sounding time, instructions to cause the wirelesscommunications device to estimate net throughput over time following thechannel sounding protocol, instructions to cause the wirelesscommunications device to identify a time corresponding to a maximum netthroughput, and instructions to cause the wireless communications deviceto determine a sounding interval corresponding to a period of timebetween an end of the sounding protocol and the time corresponding tothe maximum net throughput. Further, the storage medium may includeinstructions to cause the wireless communications device to defining aplurality of bins beginning with a first bin and extending from the endof the sounding protocol.

In one aspect, the instructions to cause the wireless communicationsdevice to estimate net throughput over time may include instructions tocause the wireless communications device to estimate a number of bitsthat may be successfully transmitted in each bin, instructions to causethe wireless communications device to select a second bin subsequent tothe first bin, instructions to cause the wireless communications deviceto sum bits that may be successfully transmitted during the first bin,during the second bin and during any intervening bins between the firstbin and the second bin and instructions to cause the wirelesscommunications device to divide the summed bits by a duration of timeextending from the first bin to the second bin plus the sounding time.Further, the instructions to cause the wireless communications device toidentify the time corresponding to the maximum net throughput mayinclude instructions to cause the wireless communications device toselect the second bin such that net throughput at the second bin is themaximum net throughput.

In one embodiment, the instructions to cause the wireless communicationsdevice to estimate the number of bits that may be successfullytransmitted in each bin may include instructions to cause the wirelesscommunications device to statistically determine a goodput for each bin.As such, the instructions to cause the wireless communications device todetermine goodput may include instructions to cause the wirelesscommunications device to transmit a first plurality of packets ofinformation over at least one preceding sounding interval initiated byperforming a sounding protocol, wherein each packet has a transmissiontime, is addressed to at least one station and is transmitted in atleast one MIMO mode, instructions to cause the wireless communicationsdevice to bin each packet of information in one bin of the plurality ofbins based, at least in part, on the transmission time of each packetrelative to the sounding protocol of the at least one preceding soundinginterval, and instructions to cause the wireless communications deviceto determine a goodput value corresponding to the bin, the station andthe MIMO mode for each packet that is acknowledged.

In a further aspect, the instructions to cause the wirelesscommunications device to determine the sounding interval may includeinstructions to cause the wireless communications device to multiply anumber of bins between the first bin and the second bin, inclusive, by aduration of each bin.

BRIEF DESCRIPTION OF THE DRAWINGS

Further features and advantages will become apparent from the followingand more particular description of the preferred embodiments of theinvention, as illustrated in the accompanying drawings, and in whichlike referenced characters generally refer to the same parts or elementsthroughout the views, and in which:

FIG. 1 schematically depicts a MIMO wireless communications system,according to one embodiment;

FIG. 2 schematically depicts functional blocks of a MIMO access pointand MIMO station, according to one embodiment;

FIG. 3 depicts a format of a PPDU containing an A-MPDU;

FIG. 4 is a flowchart showing an exemplary routine for determininggoodput statistics based on acknowledged packet transmissions, accordingto one embodiment;

FIG. 5 depicts net throughput over time as used to determine a soundinginterval in a static channel, according to one embodiment;

FIG. 6 depicts net throughput over time as used to determine a soundinginterval in a time-varying channel, according to one embodiment;

FIG. 7 is a flowchart showing an exemplary routine for determining asounding interval, according to one embodiment; and

FIG. 8 is a flowchart showing an exemplary routine for selecting a MIMOmode to be used for transmission, according to one embodiment.

DETAILED DESCRIPTION

At the outset, it is to be understood that this disclosure is notlimited to particularly exemplified materials, architectures, routines,methods or structures as such may vary. Thus, although a number of suchoptions, similar or equivalent to those described herein, can be used inthe practice or embodiments of this disclosure, the preferred materialsand methods are described herein.

It is also to be understood that the terminology used herein is for thepurpose of describing particular embodiments of this disclosure only andis not intended to be limiting.

The detailed description set forth below in connection with the appendeddrawings is intended as a description of exemplary embodiments of thepresent invention and is not intended to represent the only exemplaryembodiments in which the present invention can be practiced. The term“exemplary” used throughout this description means “serving as anexample, instance, or illustration,” and should not necessarily beconstrued as preferred or advantageous over other exemplary embodiments.The detailed description includes specific details for the purpose ofproviding a thorough understanding of the exemplary embodiments of thespecification. It will be apparent to those skilled in the art that theexemplary embodiments of the specification may be practiced withoutthese specific details. In some instances, well known structures anddevices are shown in block diagram form in order to avoid obscuring thenovelty of the exemplary embodiments presented herein.

In this specification and in the claims, it will be understood that whenan element is referred to as being “connected to” or “coupled to”another element, it can be directly connected or coupled to the otherelement or intervening elements may be present. In contrast, when anelement is referred to as being “directly connected to” or “directlycoupled to” another element, there are no intervening elements present.

Some portions of the detailed descriptions which follow are presented interms of procedures, logic blocks, processing and other symbolicrepresentations of operations on data bits within a computer memory.These descriptions and representations are the means used by thoseskilled in the data processing arts to most effectively convey thesubstance of their work to others skilled in the art. In the presentapplication, a procedure, logic block, process, or the like, isconceived to be a self-consistent sequence of steps or instructionsleading to a desired result. The steps are those requiring physicalmanipulations of physical quantities. Usually, although not necessarily,these quantities take the form of electrical or magnetic signals capableof being stored, transferred, combined, compared, and otherwisemanipulated in a computer system.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise as apparent from the followingdiscussions, it is appreciated that throughout the present application,discussions utilizing the terms such as “accessing,” “receiving,”“sending,” “using,” “selecting,” “determining,” “normalizing,”“multiplying,” “averaging,” “monitoring,” “comparing,” “applying,”“updating,” “measuring,” “deriving” or the like, refer to the actionsand processes of a computer system, or similar electronic computingdevice, that manipulates and transforms data represented as physical(electronic) quantities within the computer system's registers andmemories into other data similarly represented as physical quantitieswithin the computer system memories or registers or other suchinformation storage, transmission or display devices.

Embodiments described herein may be discussed in the general context ofprocessor-executable instructions residing on some form ofprocessor-readable medium, such as program modules, executed by one ormore computers or other devices. Generally, program modules includeroutines, programs, objects, components, data structures, etc., thatperform particular tasks or implement particular abstract data types.The functionality of the program modules may be combined or distributedas desired in various embodiments.

In the figures, a single block may be described as performing a functionor functions; however, in actual practice, the function or functionsperformed by that block may be performed in a single component or acrossmultiple components, and/or may be performed using hardware, usingsoftware, or using a combination of hardware and software. To clearlyillustrate this interchangeability of hardware and software, variousillustrative components, blocks, modules, circuits, and steps have beendescribed above generally in terms of their functionality. Whether suchfunctionality is implemented as hardware or software depends upon theparticular application and design constraints imposed on the overallsystem. Skilled artisans may implement the described functionality invarying ways for each particular application, but such implementationdecisions should not be interpreted as causing a departure from thescope of the present invention. Also, the exemplary wirelesscommunications devices may include components other than those shown,including well-known components such as a processor, memory and thelike.

The techniques described herein may be implemented in hardware,software, firmware, or any combination thereof, unless specificallydescribed as being implemented in a specific manner. Any featuresdescribed as modules or components may also be implemented together inan integrated logic device or separately as discrete but interoperablelogic devices. If implemented in software, the techniques may berealized at least in part by a non-transitory processor-readable storagemedium comprising instructions that, when executed, performs one or moreof the methods described above. The non-transitory processor-readabledata storage medium may form part of a computer program product, whichmay include packaging materials.

The non-transitory processor-readable storage medium may comprise randomaccess memory (RAM) such as synchronous dynamic random access memory(SDRAM), read only memory (ROM), non-volatile random access memory(NVRAM), electrically erasable programmable read-only memory (EEPROM),FLASH memory, other known storage media, and the like. The techniquesadditionally, or alternatively, may be realized at least in part by aprocessor-readable communication medium that carries or communicatescode in the form of instructions or data structures and that can beaccessed, read, and/or executed by a computer or other processor.

The various illustrative logical blocks, modules, circuits andinstructions described in connection with the embodiments disclosedherein may be executed by one or more processors, such as one or moredigital signal processors (DSPs), general purpose microprocessors,application specific integrated circuits (ASICs), application specificinstruction set processors (ASIPs), field programmable gate arrays(FPGAs), or other equivalent integrated or discrete logic circuitry. Theterm “processor,” as used herein may refer to any of the foregoingstructure or any other structure suitable for implementation of thetechniques described herein. In addition, in some aspects, thefunctionality described herein may be provided within dedicated softwaremodules or hardware modules configured as described herein. Also, thetechniques could be fully implemented in one or more circuits or logicelements. A general purpose processor may be a microprocessor, but inthe alternative, the processor may be any conventional processor,controller, microcontroller, or state machine. A processor may also beimplemented as a combination of computing devices, e.g., a combinationof a DSP and a microprocessor, a plurality of microprocessors, one ormore microprocessors in conjunction with a DSP core, or any other suchconfiguration.

For purposes of convenience and clarity only, directional terms, such astop, bottom, left, right, up, down, over, above, below, beneath, rear,back, and front, may be used with respect to the accompanying drawingsor particular embodiments. These and similar directional terms shouldnot be construed to limit the scope of the invention in any manner andmay change depending upon context. Further, sequential terms such asfirst and second may be used to distinguish similar elements, but may beused in other orders or may change also depending upon context.

Embodiments are described herein with regard to a wirelesscommunications device, which may include any suitable type of userequipment, such as a system, subscriber unit, subscriber station, mobilestation, mobile wireless terminal, mobile device, node, device, remotestation, remote terminal, terminal, wireless communication device,wireless communication apparatus, user agent, or other client devices.Further examples of a wireless communications device include mobiledevices such as a cellular telephone, cordless telephone, SessionInitiation Protocol (SIP) phone, smart phone, wireless local loop (WLL)station, personal digital assistant (PDA), laptop, handheldcommunication device, handheld computing device, satellite radio,wireless modem card and/or another processing device for communicatingover a wireless system. Moreover, embodiments may also be describedherein with regard to an access point (AP). An AP may be utilized forcommunicating with one or more wireless nodes and may be termed also becalled and exhibit functionality associated with a base station, node,Node B, evolved NodeB (eNB) or other suitable network entity. An APcommunicates over the air-interface with wireless terminals. Thecommunication may take place through one or more sectors. The AP may actas a router between the wireless terminal and the rest of the accessnetwork, which may include an Internet Protocol (IP) network, byconverting received air-interface frames to IP packets. The AP may alsocoordinate management of attributes for the air interface, and may alsobe the gateway between a wired network and the wireless network.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one having ordinaryskill in the art to which the disclosure pertains.

Finally, as used in this specification and the appended claims, thesingular forms “a, “an” and “the” include plural referents unless thecontent clearly dictates otherwise.

To help illustrate the systems and methods of this disclosure, anexemplary multiple-input multiple-output (MIMO) wireless communicationsystem 100 is shown in FIG. 1, including access point (AP) 102. Anaccess point is generally a fixed station that communicates with theuser terminals and may also be referred to as a base station or someother terminology. As shown, AP 102 communicates with one or morestations (STAs), such as STA 104, STA 106 and STA 108. A station may bealso be referred to as a user terminal, a wireless device, or any othersuitable terminology. For simplicity, one AP and three stations areshown, but the techniques of this disclosure may be applied to any othersuitable number of network nodes. AP 102 may communicate with one ormore user terminals at any given moment on the downlink and uplink. Thedownlink (i.e., forward link) is the communication link from AP 102 toSTAs 104, 106 and 108, and the uplink (i.e., reverse link) is thecommunication link from STAs 104, 106 and 108 to AP 102.

MIMO system 100 employs multiple transmit and multiple receive antennasfor data transmission on the downlink and uplink. AP 102 may include nantennas to provide multiple-input (MI) for downlink transmissions andthe multiple-output (MO) for uplink transmissions. A selected subset ofany stations associated with AP 102 may provide the MO for downlinktransmissions and the MI for uplink transmissions. In some embodiments,the subset of stations may include up to n stations, althoughmultiplexing techniques may be employed to increase the number ofstations in the subset. The stations in the selected subset may have thesame number or a different number of antennas.

Additional details regarding embodiments of AP 102 and STA 104 aredepicted as high level schematic blocks in FIG. 2. Although not shown,STAs 106 and 108 may be similarly configured. AP 102 may be atransmitting entity for the downlink and a receiving entity for theuplink while STA 104 may be a transmitting entity for the uplink and areceiving entity for the downlink. As used herein, a “transmittingentity” is an independently operated apparatus or device capable oftransmitting data via a wireless channel, and a “receiving entity” is anindependently operated apparatus or device capable of receiving data viaa wireless channel. Beam-steering or another suitable spatial processingtechnique may be used by AP 102 and STAs 104. On the downlink, TX dataprocessor 202 of AP 102 receives traffic data from data source 204 andsignaling and other data from a controller 206. TX data processor 202may format, encode, interleave, and modulate (or symbol map) thedifferent types of data and provide data symbols. In turn, TX spatialprocessor 208 performs spatial processing on the data symbols from TXdata processor 202, multiplexes in pilot symbols as appropriate (e.g.,for channel estimation, calibration, and so on), performs scaling with acorrection matrix (if applicable), and provides n streams of transmitsymbols to transmitter units 210 a through 210 n. Each transmitter unit210 conditions a respective transmit symbol stream to generate acorresponding downlink signal. The downlink signals from transmitterunits 210 are then transmitted from n antennas 212 a through 212 n.

Correspondingly, STA 104 includes m antennas 214 a through 214 m,wherein m may be one or more, that may receive the downlink signals,such that each antenna provides a received signal to respective receiverunits 216 a through 216 m. Each receiver unit 216 performs processingcomplementary to that performed at transmitter units 210 and providesreceived symbols. RX spatial processor 218 may perform scaling with acorrection matrix (if applicable) and further performs receiver spatialprocessing on the received symbols from all m receiver units 216 toobtain detected symbols, which are estimates of the data symbols sent byAP 102. RX data processor 220 demodulates (or symbol demaps),deinterleaves, and decodes the detected symbols and provides decodeddata to data sink 222 for storage and/or a controller 224 for furtherprocessing.

Processing for the uplink may be the same or different from theprocessing for the downlink. Data received from data source 226 andsignaling are encoded, interleaved, and modulated by TX data processor228, and further spatially processed, multiplexed with pilot symbols,and scaled with a correction matrix (if applicable) by TX spatialprocessor 230 to obtain transmit symbols. The transmit symbols arefurther processed by transmitter units 232 a through 232 m to obtain muplink signals, which are then transmitted m antennas 214 a through 214m to AP 102. At AP 102, the uplink signals are received by antennas 212,conditioned by receiver units 234 a through 234 n and processed by RXspatial processor 236 and RX data processor 238 in a mannercomplementary to that performed at STA 104 for delivery to data sink240.

Controllers 206 and 224 control the operation of various processingunits at AP 102 and STA 104, respectively. Memory units 242 and 244store data and program codes used by controllers 206 and 224,respectively. Channel estimators 246 and 248 of AP 102 and STA 104,respectively, may be configured to estimate the channel response using achannel sounding process. AP 102 may also include statistics estimator250 that provides a statistical estimate of the channel profileaccording to the techniques of this disclosure.

When employing a wireless protocol such as an Institute of Electricaland Electronics Engineers (IEEE) 802.11 standard, transmissions may beorganized into discrete units of information. Information is packetizedat an upper level of the wireless protocol stack, such as the networklayer. As the information is passed to the data link layer, the packetsor datagrams may be organized into frames having a defined format. Inone aspect, information received at the media access control (MAC)sublayer of the data link layer may be organize in MAC service dataunits (MSDUs). The MAC layer may wrap each MSDU in a MAC header to forma MAC protocol data unit (MPDU) that is delivered to the physical (PHY)layer. In turn, the PHY layer wraps the MPDU in a PHY layer convergenceprotocol (PLCP) header to form a PLCP protocol data unit (PPDU) whichmay be modulated and transmitted over the wireless medium. To reduce theframing overhead associated with wrapping each MPDU in a PLCP header,multiple MPDUs may be grouped to form an aggregate MPDU (A-MPDU), whichrequires only one PCLP header. Under current standards, an A-MPDU maycontain 64 MPDUs, although the techniques of this disclosure are notlimited in this respect.

An exemplary format of a PPDU formed from an A-MPDU is depicted in FIG.3. As shown, PPDU 300 includes PLCP header 302 and A-MPDU frame body304, which includes one or more subframes, such as subframe 1 through n.Further, each subframe includes an MPDU so that A-MPDU frame body 304has n MPDUs. For example, Subframe 2 306 is formed from MPDU 308 andbounded by delimiter 310 and padding 312 as warranted to align with aninterleaved symbol boundary.

In the context of MIMO system 100, transmissions from AP 102 to one ofSTA 104, 106 or 108 may be termed single-user MIMO (SU MIMO) when theMPDU or the entire A-MPDU is devoted to a single station. Since themultiple transmit chains may each carry a data stream for the singleuser, the data rate in SU MIMO mode may be increased as compared toconventional wireless communications systems. Alternatively,transmissions from AP 102 to two or more of STAs 104, 106 and 108, ormore generally to the selected subset of associated stations, employ anA-MPDU formed from MPDUs designated for each station in the subset andmay be termed multi-user MIMO (MU MIMO). Although only some of the datain each A-MPDU is intended for a given station, the gain in diversityrepresented by the use of multiple antennas may provide increasedreliability and capacity. MU MIMO may be further characterized by thenumber of users included in the transmission. For example, transmissionof an A-MPDU by AP 102 having one or more MPDUs for STA 104 and one ormore MPDUs for STA 106 may be termed two-user MU MIMO (MU2 MIMO) modewhile transmission of an A-MPDU by AP 102 having one or more MPDUs forSTA 104, one or more MPDUs for STA 106 and one or more MPDUs for STA 108may be termed three-user MU MIMO (MU3 MIMO) mode. In general, the MUMIMO mode may be characterized by the number of intended receivingstations.

To provide statistical information regarding performance of the MIMOsystem, statistics estimator 250 of AP 102 may be configured to generateand update a table of entries corresponding to a given characteristic ofthe operation of MIMO system 100. In one aspect, the characteristic maybe related to throughput, as throughput is an important performancemetric and optimizing throughput may often be a goal. In particular,throughput may be expressed in terms of goodput, such that goodputreflects the throughput experienced by the receiver less any overheadassociated with the communications systems and an errors occurringduring transmission.

A common aspect shared by wireless communication systems is that theenvironment may be constantly changing, as a result of relative motionbetween nodes in the network, varying multipath effects and otherfactors. Due to the complexity associated with providing multipletransmit streams having adjusted phase and amplitude, MIMO system 100may employ a closed-loop beamforming system to help provide currentchannel state information (CSI). For example, channel estimators 246 and248 may employ a sounding protocol, in which a known pattern ofinformation is sent periodically. The time period between soundingevents may be termed a “sounding interval.” By analyzing characteristicsof the signal appearing at the receiver, CSI may be determined and fedback to transmitter units 208 and 232. Due to the time varying nature ofthe channel, the CSI may be most accurate immediately following thesounding transmission and, depending upon how static the channel is, maydegrade more slowly or more quickly over time. Since the performance ofMIMO system 100 may depend upon the accuracy of the CSI used to controlthe transmitters, it may also degrade over the sounding interval.

Accordingly, statistics estimator 250 may be configured to correlatedetermined goodput over time, relative to the last channel soundingtransmission. In one aspect, a plurality of sequential bins 1 through k,each having a defined duration D, may be established following eachchannel sounding event. Together, bins 1 through k may correspond to orextend beyond a given sounding interval. The duration D may be selectedso that the channel does not vary too significantly during each bin. Forexample, a suitable duration D may be approximately 2 ms. Statisticsestimator 250 may assign each MPDU transmitted by AP 102, sent either asa single MPDU or as part of an A-MPDU, to one of the bins depending uponthe transmission time relative to the last sounding event.

In turn, for each bin, statistics estimator 250 may determine a goodputfor each station, such as STAs 104, 106 and 108, based uponacknowledgement communications. For example, a receiving station maytransmit an acknowledgement (ACK) for each MPDU successfully received.To accommodate the multiple MPDUs transmitted in an A-MPDU, thereceiving stations may employ a block acknowledgement (BA) process.Rather than transmitting an individual ACK for every MPDU, the successor failure of multiple MPDUs addressed to a given station may beacknowledged with a BA frame, having a bitmap indicating the success orfailure of reception of each MPDU. The PHY and MAC layers of AP 102employ the ACK and BA communications to identify MPDUs that were notsuccessfully received and may require retransmission. By obtaining theACK and BA information from transmitter units 210, statistics estimator250 may estimate goodput based on the size of acknowledged MPDUs and aninstantaneous packet error rate (PER) for unacknowledged MPDUs for eachbin and each station.

Further, a performance characteristic such as goodput may also dependupon the MIMO mode used by AP 102 to transmit the information. As notedabove, the SU MIMO mode may be tailored to provide increased data ratewhile the MU MIMO modes may provide increased reliability. Therefore,statistics estimator 250 may also be configured to classify the goodputfor each station on the basis of MIMO mode. In this manner, a channelprofile based on goodput statistics for each MIMO mode may be obtained.

In one aspect, statistics estimator 250 may determine a goodput valuefor each MIMO mode of each station for each bin. For example, statisticsestimator 250 may maintain a goodput table having entries in the form ofa 3-tuple: Goodput(userID, mode, bin), wherein userID may identify thestation, mode may identify the SU or MU MIMO mode and bin may identifythe bin number.

In another aspect, statistics estimator 250 may use information from thegoodput table to provide a quantized goodput profile for each station.For example, performance in a given MIMO mode may be expressed as aprofile score that represents the length of time required for thedetermined goodput to decrease by a predetermined percentage, such as50%, from a peak value. Any other suitable integration or quantizationof the goodput values determined by statistics estimator 250 may be usedas desired. Further, the profile score for each mode may be weighted bya suitable coefficient and summed to derive an overall profile score fora given station. By analyzing changes to the overall profile score overtime, the channel variations for the station may be determined.

As noted, statistics estimator 250 may populate the goodput table byassigning MPDUs to one of the k bins based upon the transmit timerelative to the last sounding event. Correspondingly, it may bedesirable to update one or more of the 3-goodput entries using a goodputvalues calculated from one or more MPDUs transmitted in subsequentsounding intervals. The entries may be updated as desired with morerecently-determined goodput information using any suitable finite orinfinite impulse filter, of any order. In one embodiment, the entriesmay be updated using equation (1):Goodput(userId,mode,bin)=a*Goodput(userId,mode,bin)+(1−a)*LatestGoodput(userId,mode,bin)  (1)The coefficient a may be selected to determine the rate at which thetable reacts to newly-determined goodput values. Relatively largervalues of a may be employed to slow the rate of change of table entriesto accommodate short duration shadowing or brief interference eventswhile relatively smaller values of a may be employed to achieve a morereactive table to accommodate rapidly changing channel conditions, suchas in an environment experiencing frequent switches between static andmobile conditions.

In another aspect, MIMO system 100 may employ varying communicationstrategies, particularly in response to changing channel conditions suchas between mobile and static. As a result, MPDUs may not be evenlyspread across the bins for all stations and all MIMO modes during agiven sounding interval. Useful characterization may still be made forbins that are not directly populated by information based upon receivedacknowledgements. As desired, table entries that do not have dataderived directly from an acknowledged MPDU may be populated with deriveddata interpolated or extrapolated from one or more adjacent bins at theend of each sounding interval. These entries may be determined using anysuitable technique, including, e.g., polynomial fit routines,generalized function learning procedures or linear combinations ofexponential functions. An extrapolated or interpolated entry may also beupdated or used to update an entry using any suitable filteringtechnique, as described above.

Further, statistics estimator 250 may determine the goodput statisticsfrom information readily available at the PHY layer of transmitter units210. Since characteristics such as the size and transmission time foreach MPDU and any corresponding acknowledgments received from theassociated stations are known, statistics estimator 250 may beimplemented in upper levels of the WLAN protocol stack, such as throughsoftware routines performed by controller 206. Accordingly, thetechniques of this disclosure impart little or no additional overhead onthe WLAN hardware.

To help illustrate the techniques of this disclosure with regard todetermining a statistical channel profile, an exemplary routine isrepresented in the flowchart of FIG. 4. Beginning with 402, a wirelesscommunications device may transmit a first packet of information to afirst station using a first MIMO mode at a first transmission time. Inthe context of MIMO system 100, the wireless communications device maybe AP 102 and the first station may be one of STAs 104, 106 and 108. Asnoted above, the packet of information may be an MPDU addressed to thefirst station or may be a subframe of an A-MPDU containing an MPDUaddressed to the first station. Depending upon the wireless protocolbeing employed, other packet formats may be used as desired. In 404,statistics estimator 250 may bin (place) the first packet in a first binbased, at least in part, on the first transmission time relative to aperiodically recurring event, such as the transmission of soundinginformation. Next, in 406, statistics estimator 250 may determine thatthe first station has acknowledged receipt of the first packet. Usingthe acknowledgement, statistics estimator 250 may calculate a goodputvalue for the first bin, the first MIMO mode and the first station in408. Statistics estimator 250 may repeat 402 through 408 for a pluralityof packets sent over an interval defined by the periodically recurringevent, such as a sounding interval as indicated by 410.

Additionally, statistics estimator 250 may generate a goodput table in412, which includes entries for each bin, each station and each MIMOmode, with the entries populated by the goodput values determined fromacknowledged packets. When a plurality of goodput values exist for agiven entry, such as when more than one acknowledged MPDU for a givenstation in a given mode is sent during one bin, the goodput values maybe combined to provide the total goodput for that bin. For any goodputtable entries that are not populated (for example, if no MPDU is sentduring the interval for a given combination of bin, station and mode),statistics estimator 250 may derive a goodput value using extrapolationor interpolation of values from adjacent bins as indicated by 414.Statistics estimator 250 may also determine new goodput values over oneor more subsequent intervals and may update entries in the goodput tableusing the newly determined goodput value in 416.

By expressing channel statistics in terms of goodput, behavior of MIMOsystem 100 may be adapted to improve performance, such as by optimizingthroughput or other suitable performance characteristics. For example,the goodput values determined by statistics estimator 250 may be used togroup stations experiencing a similar type of channel in a common MUMIMO mode of operation to help achieve more efficient sounding and boostthroughput. In another aspect, the goodput values determined bystatistics estimator 250 may also be used to adapt the modulation andcoding scheme based upon an estimation of the rate at which channelinformation becomes stale following a sounding event. In yet anotheraspect, AP 102 may aggregate packets within a given transmissionopportunity based upon the rate of channel change.

The relationship of goodput to throughput also allows the goodput valuesdetermined by statistics estimator 250 to be used to estimate netthroughput. In turn, net throughput may be used in various applications.For example, a MIMO system may offer a choice of antenna sets to use. Bydeveloping goodput statistics for each combination, selection ofantennas may be optimized.

In one embodiment, the goodput values determined by statistics estimator250 may be used to determine a sounding interval that improvesperformance. As will be described below, net throughput over time may beestimated. Then, an improved (and/or optimized) sounding interval may bedetermined by identifying a period of time that maximizes netthroughput. While the below description uses the term “optimized,”various embodiments of the disclosure may use any improved soundinginterval that may not be “optimized” under the general meaning of theterm. Therefore, the below examples and the disclosure in general shouldnot be limited by use of such term.

First, statistics estimator 250 may estimate net throughput over timebased on the determined goodput values. Net throughput achieved througha given bin l, wherein l≦k, may be determined by summing the amount ofdata successfully transmitted during each bin, from 1 to l, and dividingby the elapsed time through bin 1, including the time required for thesounding process. The goodput statistics for each bin may be used toestimate the data successfully sent during each bin. One suitableformulation of this calculation is given by equation (2):Net_thrpt(l)=Sum(i=1:l)Succ_Bits(i)/(l*D+sounding_time),  (2)wherein D is the length of each bin, Succ_Bits(i) is an estimation ofthe amount of information that may be successfully transmitted duringeach bin for all stations and in all MIMO modes as calculated from thedetermined goodput values, and sounding_time is the amount of timerequired to transmit the sounding pattern, which may be calculated fromthe data rate being employed to transmit the sounding pattern.

A graph of net throughput over time may produce a generally concavecurve in which the net throughput will rapidly increase after completionof the sounding process and successful transmission of data commences,overcoming the overhead associated with sounding. Next, the netthroughput may approach a maximum that depends upon the theoreticalthroughput that may be achieved given the capabilities of MIMO system100. The behavior of the curve following the initial rapid rise maydepend upon characteristics of the channel. Accordingly, statisticsestimator 250 may be configured to determine the lth bin at which netthroughput is maximized. Correspondingly, the sounding may be optimizedby selecting a sounding interval corresponding to the period of timefrom the end of the sounding process until the lth bin. One suitableformulation of this calculation is given by equation (3):SI_opt=argmax(Net_throughput(l))*D  (3)

For example, FIG. 5 depicts a channel in a generally static condition.As shown, net throughput may reach a maximum throughput 502corresponding to bin l. Optimized sounding interval 504 may bedetermined based on the period between the end of sounding process 506and maximum throughput 502. Due to the static nature of the channel, itmay remain constant for a relatively longer period of time. Thus, thechannel estimation performed during sounding continues to be valid sothat net throughput may remain relatively constant, by either graduallyapproaching the asymptote of time instant 502 or gradually decreasing asthe channel changes over time.

In comparison, FIG. 6 depicts a more rapidly changing channel, such asmay be experienced in a high Doppler environment resulting from relativemotion between AP 102 and STAs 104, 106 and 108. As shown, netthroughput may reach a maximum throughput 602 corresponding to bin l.Optimized sounding interval 604 may be determined based on the periodbetween the end of sounding process 606 and maximum throughput 602. Inthis example, the channel estimate may become less accurate more quicklysuch that the net throughput degrades relatively rapidly over time aftermaximum throughput 602 is reached.

To help illustrate the techniques of this disclosure with regard todetermining an optimized sounding interval, an exemplary routine isrepresented by the flowchart of FIG. 7. Beginning with 702, a wirelesscommunications device such as AP 102 may perform a channel soundingprotocol. Next, in 704, statistics estimator 250 may be configured toestimate net throughput over a period of time commencing at an end ofthe channel sounding protocol. In one embodiment, net throughput may beestimated based on the determined goodput values as described above.Statistics estimator 250 may then identify a time instant correspondingto a maximum net throughput in 706 and correspondingly determine theoptimized sounding interval in 708.

In another embodiment, AP 102 may employ the goodput values determinedby statistics estimator 250 to select between the SU MIMO mode and MUMIMO modes when scheduling a packet for transmission to one of STAs 104,106 and 108 to improve overall performance of MIMO system 100.Generally, statistics estimator 250 may estimate a net goodput that maybe achieved using each of the available MIMO modes and AP 102 may selectthe MIMO mode associated with a desired net goodput, such as thegreatest net goodput.

Statistics estimator 250 may determine net goodput for a given MIMO modeby calculating the amount of scheduled data that may be delivered to oneof STAs 104, 106 and 108 over an upcoming sounding interval. Thesounding interval may be determined from the goodput statistics asdescribed above or may be determined using any other suitable method.Net goodput for a given MIMO mode and station may be the amount of datathat may be delivered divided by the transmission time required todeliver the data and the overhead time associated with the soundingprotocol. One formulation for determining net goodput is given byequation (4):Net_goodput(mode)=Total_Succ_Bits(mode)/(Total_PPDU_time+sounding_time)  (4)wherein Total_Succ_Bits is an estimate of the total amount of data to bedelivered, Total_PPDU_time is the transmission time for the packets andsounding_time is the amount of time required to transmit the soundingpattern, which may be calculated from the data rate being employed totransmit the sounding pattern.

The total amount of data and PPDU transmission time used to estimate netgoodput may be related to the total number of packets N that may bedelivered during the next sounding interval. During operation of MIMOsystem 100, a transmit opportunity with regard to a given station may beawarded in a round-robin manner. Depending upon the usage rate of thewireless medium, one or more transmit opportunities may be awarded withregard to the given station during a sounding interval. The time betweentransmit opportunities may be termed a “round-robin interval” and may bedetermined based upon information gathered during a recent soundinginterval. As such, the ratio of sounding interval to round-robininterval may be used to estimate the number of transmit opportunities inan upcoming sounding interval. Based on the number of transmitopportunities, statistics estimator 250 may also estimate the number ofpackets that may be transmitted to a station in SU MIMO mode.

Further, when operating in a MU MIMO mode, AP 102 may transmit apredetermined number of packets in a “burst” at each transmitopportunity. In such modes, the total number of packets that may bedelivered may be determined by multiplying the number of packets in aburst by the number of transmit opportunities.

Alternatively, the length of the transmit queue of AP 102 may limit thedata to be delivered, such that the total number of packets that may bedelivered during the upcoming sounding interval may correspond to thelength of the transmit queue in terms of packets. As a result, the totalnumber of packets that will be delivered may be the minimum of either ofthese determinations.

Accordingly, in one embodiment the total number of packets N that may besent is given by equation (5):N=Min(Q,ceiling(S/R)*B)  (5)wherein Q is the length of the transmit queue for the given station interms of packets, S is the sounding interval, R is the round-robininterval and B is the number of packets in a MU MIMO burst or is one forSU MIMO.

Once statistics estimator 250 has estimated the total number of packetsthat may be delivered in the upcoming sounding interval, the totalamount of data delivered may be calculated based upon the goodputstatistics accumulated over previous sounding intervals and thetransmission time may be determined from a rate control table. In turn,statistics estimator 250 may determine the net goodput for a given modeof operation of a station such that AP 102 may select the MIMO mode ofoperation that provides a desired net goodput.

To help illustrate the techniques of this disclosure with regard toscheduling SU MIMO and MU MIMO modes of operation, an exemplary routineis represented by the flowchart of FIG. 8. Beginning with 802, awireless communications device such as AP 102 may determine a length ofan upcoming sounding interval. Next, in 804, statistics estimator 250may be configured to estimate a number of packets that may be deliveredto a station during the upcoming sounding interval. In one embodiment,the number of packets may be estimated using the determined goodputvalues as described above. Further, the number of packets may beestimated based on the number of packets in a multi user (MU) MIMO burstmultiplied by a ratio of sounding interval to round-robin interval orbased on the length of the transmit queue for the station. Statisticsestimator 250 may then determine the net goodput for the station at eachof a plurality of MIMO operating modes in 806 and AP 102 may schedule atransmission based on a desired net goodput in 708.

Described herein are presently preferred embodiments. However, oneskilled in the art that pertains to the present invention willunderstand that the principles of this disclosure can be extended easilywith appropriate modifications to other applications.

What is claimed is:
 1. A method for communication in a multiple inputmultiple output (MIMO) system comprising: performing a channel soundingprotocol during a first time period; defining a plurality of binsbeginning with a first bin and extending from an end of the first timeperiod; estimating net throughput during a second time period followingthe first time period by: selecting a second bin, subsequent to thefirst bin; summing bits that may be successfully transmitted during thefirst bin, the second bin, and intervening bins between the first binand the second bin; and dividing the summed bits by a duration of timeextending from the first bin to the second bin plus the first timeperiod; determining a time corresponding to a maximum net throughput,wherein the time is within the second time period; and determining asounding interval based, at least in part, on a third time periodextending between the end of the first time period and the timecorresponding to the maximum net throughput.
 2. The method of claim 1,wherein estimating net throughput during the second time periodcomprises estimating a number of bits that may be successfullytransmitted in each bin.
 3. The method of claim 1, wherein determiningthe time corresponding to the maximum net throughput comprises selectingthe second bin such that net throughput at the second bin is the maximumnet throughput.
 4. The method of claim 2, wherein estimating the numberof bits that may be successfully transmitted in each bin comprisesstatistically determining goodput for each bin.
 5. The method of claim4, wherein statistically determining goodput comprises: transmitting afirst plurality of packets of information over at least one precedingsounding interval initiated by performing a sounding protocol, whereineach packet has a transmission time, is addressed to at least onestation and is transmitted in at least one MIMO mode; binning eachpacket of information in one bin of the plurality of bins based, atleast in part, on the transmission time of each packet relative to thesounding protocol of the at least one preceding sounding interval; anddetermining a goodput value corresponding to the bin, the station andthe MIMO mode for each packet that is acknowledged.
 6. The method ofclaim 1, wherein determining the sounding interval comprises multiplyinga number of bins between the first bin and the second bin, inclusive, bya duration of each bin.
 7. A wireless communications device to operatein a multiple input multiple output (MIMO) system, comprising: a numberof transmitter units to transmit a channel sounding protocol during afirst time period; and a statistics estimator to: define a plurality ofbins beginning with a first bin and extending from an end of the firsttime period; estimate net throughput during a second time periodfollowing the first time period by: selecting a second bin subsequent tothe first bin; summing bits that may be successfully transmitted duringthe first bin, the second bin and intervening bins between the first binand the second bin; and dividing the summed bits by a duration of timeextending from the first bin to the second bin plus the first timeperiod; determine a time corresponding to a maximum net throughput,wherein the time is within the second time period; and determine asounding interval based, at least in part, on a third time periodextending between the end of the first time period and the timecorresponding to the maximum net throughput.
 8. The wirelesscommunications device of claim 7, wherein the statistics estimator is toestimate net throughput during the second time period by estimating anumber of bits that may be successfully transmitted in each bin.
 9. Thewireless communications device of claim 7, wherein the statisticsestimator is to determine the time corresponding to the maximum netthroughput by selecting the second bin such that net throughput at thesecond bin is the maximum net throughput.
 10. The wirelesscommunications device of claim 8, wherein the statistics estimator is toestimate the number of bits that may be successfully transmitted in eachbin based, at least in part, on a statistically determined goodput foreach bin.
 11. The wireless communications device of claim 10, whereinthe transmitter units are to transmit a first plurality of packets ofinformation over at least one preceding sounding interval initiated byperforming a sounding protocol, wherein each packet has a transmissiontime, is addressed to at least one station and is transmitted in atleast one MIMO mode; and wherein the statistics estimator is todetermine goodput by: binning each packet of information in one bin ofthe plurality of bins based, at least in part, on the transmission timeof each packet relative to the sounding protocol of the at least onepreceding sounding interval; and determining a goodput valuecorresponding to the bin, the station and the MIMO mode for each packetthat is acknowledged.
 12. The wireless communications device of claim 7,wherein the statistics estimator is to determine the sounding intervalby multiplying a number of bins between the first bin and the secondbin, inclusive, by a duration of each bin.
 13. A non-transitoryprocessor-readable storage medium for operating a multiple inputmultiple output (MIMO) wireless communications device, theprocessor-readable storage medium storing instructions that, whenexecuted by a processor, cause the wireless communications device to:perform a channel sounding protocol during a first time period; define aplurality of bins beginning with a first bin and extending from an endof the first time period; estimate net throughput during a second timeperiod following the first time period by: selecting a second binsubsequent to the first bin; summing bits that may be successfullytransmitted during the first bin, the second bin and intervening binsbetween the first bin and the second bin; and dividing the summed bitsby a duration of time extending from the first bin to the second binplus the first time period; determine a time corresponding to a maximumnet throughput, wherein the time is within the second time period; anddetermine a sounding interval based, at least in part, on a third timeperiod extending between the end of the first time period and the timecorresponding to the maximum net throughput.
 14. The storage medium ofclaim 13, wherein the instructions to cause the wireless communicationsdevice to estimate net throughput during the second time periodcomprises instructions to cause the wireless communications device toestimate a number of bits that may be successfully transmitted in eachbin.
 15. The storage medium of claim 13, wherein the instructions tocause the wireless communications device to determine the timecorresponding to the maximum net throughput comprises instructions tocause the wireless communications device to select the second bin suchthat net throughput at the second bin is the maximum net throughput. 16.The storage medium of claim 14, wherein the instructions to cause thewireless communications device to estimate the number of bits that maybe successfully transmitted in each bin comprises instructions to causethe wireless communications device to statistically determine a goodputfor each bin.
 17. The storage medium of claim 16, wherein theinstructions to cause the wireless communications device tostatistically determine goodput comprises: instructions to cause thewireless communications device to transmit a first plurality of packetsof information over at least one preceding sounding interval initiatedby performing a sounding protocol, wherein each packet has atransmission time, is addressed to at least one station and istransmitted in at least one MIMO mode; instructions to cause thewireless communications device to bin each packet of information in onebin of the plurality of bins based, at least in part, on thetransmission time of each packet relative to the sounding protocol ofthe at least one preceding sounding interval; and instructions to causethe wireless communications device to determine a goodput valuecorresponding to the bin, the station and the MIMO mode for each packetthat is acknowledged.
 18. The storage medium of claim 13, wherein theinstructions to cause the wireless communications device to determinethe sounding interval comprises instructions to cause the wirelesscommunications device to multiply a number of bins between the first binand the second bin, inclusive, by a duration of each bin.